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Fast Response or Silence: Conversation Persistence in an AI-Agent Social Network

Aysajan Eziz

arXiv 7 Feb 2026 · Econometrics

arXiv:2602.07667 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Autonomous AI agents are beginning to populate social platforms, but it is still unclear whether they can sustain the back-and-forth needed for extended coordination. We study Moltbook, an AI-agent social network, using a first-week snapshot and introduce interaction half-life: how quickly a comment's chance of receiving a direct reply fades as the comment ages. Across tens of thousands of commented threads, Moltbook discussions are dominated by first-layer reactions rather than extended chains. Most comments never receive a direct reply, reciprocal back-and-forth is rare, and when replies do occur they arrive almost immediately -- typically within seconds -- implying persistence on the order of minutes rather than hours. Moltbook is often described as running on an approximately four-hour “heartbeat” check-in schedule; using aggregate spectral tests on the longest contiguous activity window, we do not detect a reliable four-hour rhythm in this snapshot, consistent with jittered or out-of-phase individual schedules. A contemporaneous Reddit baseline analyzed with the same estimators shows substantially deeper threads and much longer reply persistence. Overall, early agent social interaction on Moltbook fits a “fast response or silence” regime, suggesting that sustained multi-step coordination will likely require explicit memory, thread resurfacing, and re-entry scaffolds.

Citation extraction

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appendix boundary found by appendix_titled_section at “S1. Mathematical Framework and Proofs” · 70% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1SimulaMet (2026) Moltbook Observatory Archive [Data set]0.92843100%
2Jouini, Oualid and Pot, Auke and Koole, Ger and Dallery, Yves (2010) Online scheduling policies for multiclass call centers with impatient customers0.73732100%
3Whitt, Ward (2004) Efficiency-Driven Heavy-Traffic Approximations for Many-Server Queues with Abandonments0.73732100%
4Aragon, Pablo and Gomez, Vicen c and Kaltenbrunner, Andreas (2017) To Thread or Not to Thread: The Impact of Conversation Threading on Online Discussion0.64422100%
5Crane, Riley and Sornette, Didier (2008) Robust dynamic classes revealed by measuring the response function of a social system0.64422100%
6Gómez, Vicen c and Kappen, Hilbert J. and Kaltenbrunner, Andreas (2011) Modeling the structure and evolution of discussion cascades0.64422100%
7Harris, Theodore E (1963) The Theory of Branching Processes0.64422100%
8Meital, Shai and Rokach, Lior and Vainshtein, Roman and Grinberg, Nir (2024) The Branch Not Taken: Predicting Branching in Online Conversations0.64422100%
9Reed, Josh and Tezcan, Tolga (2012) Hazard Rate Scaling of the Abandonment Distribution for the GI/M/n + GI Queue in Heavy Traffic0.64422100%
10Rizoiu, Marian-Andrei and Xie, Lexing and Sanner, Scott and Cebrián,… (2017) Expecting to be HIP: Hawkes intensity processes for social media popularity0.64422100%

Showing the top 10 of 17 scored citations.